Preparing glycomics data for robust statistical analysis with GlyCompareCT

Glycomics data are rapidly increasing in scale and diversity. Because glycan biosynthesis is hierarchical, competitive, and compartmentalized, preprocessing is critical to address data sparsity (similar glycosylation profiles may share few common glycans) and non-independence (substrate-competition in glycan biosynthesis results in non-independence incompatible with many statistical methods). Here we present GlyCompareCT, a portable command-line tool, to address these challenges by preparing samples for more accurate downstream analyses. Users input measured glycan abundances and GlyCompareCT conducts substructure decomposition to quantify hidden biosynthetic intermediates and relationships between all measured glycans. Thus, GlyComparCT mitigates sparsity, makes interdependence explicit, and increases statistical power. Ultimately, GlyComparCT makes large glycomic datasets accessible thus enabling or improving downstream bioinformatic analysis.